Microsoft Technology Licensing, LLC

Peter Alan Carlin

Beysim Sezgin

Jose A Blakeley

Jun Fang

Ramachandran Venkatesh

Balaji Rathakrishnan

Ajay Kalhan

Christopher Wellington Brumme

Cesar Alejandro Galindo-Legaria

Christian Kleinerman

Steven J Pratschner

Mason K Bendixen

Ian H Carmichael

Shrinivas Ashwin

WeiWen Liu

Stefano Stefani

Goetz Graefe

Per-Ake Larson

Craig C Peeper

Steven Miles Greenberg

Raja Krishnaswamy

Nigel Robin Ellis

Christopher David Brown

Alazel Acheson

Jingren Zhou

Sean Edwin Trowbridge

Shen Wang

Aleksandras Surna

Todd Haugen

Mahesh Prakriya

Ivan Dimitrov Pashov

Erik Ismert

Alan C Shi

Qun Guo

Srinivasmurthy P Acharya

Sumit Chauhan

Willis Lang

Brian Eugene Kihneman

Ganapathy Subramaniam Krishnamoorthy

Shize Xu

Suzanne Maurine Cook

Mei-Chin Tsai

Karthik Saligrama Ramachandra

Samuel H Smith

Vijayalakshmi Ramkumar

Patrick Eugene O'Neil

Elizabeth Jean O'Neil

Michael Hopkins Smith

Alexander Alexandrovich Spiridonov

Gregory L Chan

Daniel J Cole

Aditya Sharma

Tobias Joakim Bertil Ternström

Christopher Todd Seitzinger

David Michael Jade

Ritu Singh

Alexios Boukouvalas

Russell Sinclair

Kiran Kumar Venkata Purna Chenna Kesava Vemula

Arpan Kumar Gupta

Vinothkumar Prabhakaran

Girkumar Nair

Honggang Zhang

Hongang Zhang

David Johns DeWitt

Harold R Berenson

Srikanth Subramanian

Techniques for implementing a last known good (LKG) client-side cache for DNS resiliency are disclosed. A first DNS request is submitted to a DNS server. A first DNS resolution that resolves an IP address for a domain name is received. A service stores the first DNS resolution in an LKG cache residing on the local host. A second DNS request is sent, where the second DNS request again requests to resolve the same domain name. In response to determining that a second DNS resolution for the second DNS request has not been received, the service obtains the IP address for the domain name from the LKG cache.

LKG client cache for DNS resiliency

Managing cluster resources for a cluster. The method includes identifying a plurality of quiescence policies. Each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities. The method further includes, for each quiescence policy, identifying an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy. The method further includes, for each quiescence policy, identifying an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities. The method further includes; selecting a quiescence policy based on comparing the reclaimed capacities and reserve capacities for the quiescence policies. The method further includes, booking cluster resources for cluster entities on the cluster according to the selected quiescence policy.

Modeling and forecasting reserve capacity for overbooked clusters

Creating web application using cloud-based friction-free databases without web hosting knowledge. User credentials are received at a web application service for initiating a web application task via client software. The user credentials are analyzed to determine whether to grant the user permission to initiate the requested web application task. The web application task is initiated when the permission is granted. Data associated with the initiated web application task is received at the web application service for analysis of the data to host and render a web application based solely on received data provided without basis of web hosting knowledge.

Creating web applications using cloud-based friction-free databases without requiring web hosting knowledge

Systems and methods that group atomic scalar values recognized by a database such as columns into sets (e.g., column sets). A grouping component associated with the SQL server creates a logical representation for column groupings, which are accessible by a single I/O and can be co-located (e.g., substantially close or compact) in terms of storage location. Interesting column sets (e.g., non-null) can also be selected for a data representation thereof as a single entity to other applications.

Scalar representation for a logical group of columns in relational databases

This disclosure provides techniques for asynchronously maintaining database indexes or sub-indexes. For example, a database management server may receive a data manipulation statement to modify particular data stored in a database and determine whether an index associated with executing the statement is maintained asynchronously. When the index is maintained asynchronously, maintenance of the index to reflect changes made to the particular data by executing the data manipulation statement may be delayed until an index maintenance event. The index maintenance may be based on an isolation level of a transaction including a query that triggered the index maintenance.

Asynchronous database index maintenance

Various embodiments of the present invention enable functions, procedures, and triggers to be written in any of the .NET languages and executed by the RDBMS. User code can access data from the local or other SQL servers using the SQL Programming Model and both the SqlServer or SqlClient implementations respectively. Moreover, to improve upon the previous extensibility mechanism, a set of APIs (commonly known as 'the in-process provider' or 'inproc provider') is utilized to provide efficient and easy to use data access while running inproc, a data access API that is an implementation of the ADO.net programming model.

Systems and methods for a database engine in-process data provider

A database system and method allows a user to write program code in a high-level programming language that implements a class that defines the structure of a user-defined type and methods that can be invoked on instances of the type. The class is then registered with the database system, which enforces a specific contract for user-defined types against the class. The contract comprises the following requirements. First, the class must specify one of a plurality of different formats for persisting instances of the user-defined type in a database store. Second, the class must be capable of returning a null value for the user-defined type. Third, the class must provide a method for converting the user-defined type to another type. Once these requirements are satisfied, the database system enables instances of the user-defined type to be created. A user-defined type can be used in all contexts where any other built-in type can be used. This includes defining columns of tables, declaring variables and parameters to functions and stored procedures, and evaluating expressions of the user-defined type in SQL queries and updates. Preferably, the database system stores metadata about the user-defined type for subsequent use in creating instances of the type.

System and method for providing user defined types in a database system

Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) which are an internal representation of a large value. BHs are immutable and stateless references to a large data object. The structure of a BH contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.

Systems and methods for a large object infrastructure in a database system

Systems and methods for enhanced runtime hosting are described. In one aspect the runtime hosting interface includes a host abstraction interface. The HAI allowing the runtime to configure host execution environment parameters and/or notify the host of a runtime event. In particular, the host abstraction interface (HAI) corresponds to execution environment abstractions supported by a host application. Responsive to an action or event, the runtime invokes an identified HAI or an associated object during execution of runtime managed code.

Runtime hosting interfaces

Systems and methods for enhanced runtime hosting are described. In one respect, the runtime identifies any abstraction interface(s) exposed by a host application. The abstraction interface(s) correspond to respective execution environment functionality implemented by the hosting application. During execution of runtime managed code and responsive to an action or event associated with an identified one of the respective execution environment abstractions, the runtime calls a specific interface or object corresponding to a specific one of the abstraction interface(s). This allows the host application to customize/enhance its execution environment, which includes the runtime, as a function of the implemented abstraction(s).

Enhanced runtime hosting

A database system and method allows a user to write program code in a high-level programming language that implements a class that defines the structure of a user-defined aggregate and methods that can be invoked on instances of the user-defined aggregate. The class is then registered with the database system, which enforces a specific contract for user-defined aggregates against the class. The contract comprises the following requirements. First, the class must specify one of a plurality of different formats for persisting instances of the user-defined aggregate in a database store. Second, the class must comprise certain specified methods that can be invoked on an instance of the class. Once these requirements are satisfied, the database system enables instances of the user-defined aggregate to be created. Preferably, the database system stores metadata about the user-defined aggregate for subsequent use in creating instances of the aggregate.

System and method for providing user defined aggregates in a database system

Any string in any character set with an arbitrary-leveled weight-based comparison system is transformed into a bitstring in such a way that two transformed strings can be compared byte-by-byte. The resulting bit string has the minimum possible maximum length. The transformed bit strings can be inverted&#x2014;meaning the original string can be recovered from the transformed string.

Compressed normalized character comparison with inversion

An auto-parameterization process transforms a database query into a parameterized basic query form by replacing any constant values in the query with parameters. The auto-parameterization process attempts to generate a safe execution plan from the basic query form if there is currently no such plan available. A safe execution plan is defined as an execution plan that is optimal over a range of values for the parameters. If a safe execution plan can be generated, it is passed for execution, along with the constant values that were present in the query. If a safe execution plan cannot be generated, the auto-parameterization process passes a specific execution plan for execution. The safe execution plan is cached either at the time it is created or at the time it is executed. The cache is searched each time a parameterized basic query plan is generated by the auto-parameterization process. The auto-parameterization process also evaluates the query before creating the corresponding parameterized basic query form to determine if it is likely that a safe execution plan can be generated for the query.

Auto-parameterization of database queries

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Seattle, WA, United States of America

Peter Alan Carlin